The Crass ceiling: Female comedians and an analysis of sexism within stand up comedy
Bibliographic record
Abstract
This thesis examines and analyzes female comedians and the existence of gendered barriers within the stand up comedy industry. A long history of the exclusion of women from the mainstream and 'normal' spheres of life contributes, at least in part, to the perceived "otherness" of female comedy and helps to contextualize how and why women have been and continue to be considered less "funny" than men. I use a feminist standpoint methodology, incorporating 12 qualitative interviews, observations, and a quantitative content analysis of the number of men and women headliners at a comedy club in Toronto for 12 months to explore how cultural perceptions depicting men as the sole (or natural) producers of comedy have created barriers for women in comedy. Such barriers are theorized to be the crass ceiling, and explicate the strange phenomenon whereby which women are largely prevented from achieving similar levels of success than their male counterparts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".